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Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water–fat MRI
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Advanced MR Analytics AB, Linköping, Sweden.
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Center for Medical Image Science and Visualization (CMIV).
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2015 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 41, no 6, 1558-1569 p.Article in journal (Refereed) Published
Abstract [en]

Purpose

To develop and demonstrate a rapid whole-body magnetic resonance imaging (MRI) method for automatic quantification of total and regional skeletal muscle volume.

Materials and Methods

The method was based on a multi-atlas segmentation of intensity corrected water–fat separated image volumes. Automatic lean muscle tissue segmentations were achieved by nonrigid registration of atlas datasets with 10 different manually segmented muscle groups. Ten subjects scanned at 1.5 T and 3.0 T were used as atlases, initial validation and optimization. Further validation used 11 subjects scanned at 3.0 T. The automated and manual segmentations were compared using intraclass correlation, true positive volume fractions, and delta volumes.

Results

For the 1.5 T datasets, the intraclass correlation, true positive volume fractions (mean ± standard deviation, SD), and delta volumes (mean ± SD) were 0.99, 0.91 ± 0.02, −0.10 ± 0.70L (whole body), 0.99, 0.93 ± 0.02, 0.01 ± 0.07L (left anterior thigh), and 0.98, 0.80 ± 0.07, −0.08 ± 0.15L (left abdomen). The corresponding values at 3.0 T were 0.97, 0.92 ± 0.03, −0.17 ± 1.37L (whole body), 0.99, 0.93 ± 0.03, 0.03 ± 0.08L (left anterior thigh), and 0.89, 0.90 ± 0.04, −0.03 ± 0.42L (left abdomen). The validation datasets showed similar results.

Conclusion

The method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2015. Vol. 41, no 6, 1558-1569 p.
Keyword [en]
multi-atlas segmentation; muscles; registra- tion; muscle volume; classification; MRI
National Category
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-109319DOI: 10.1002/jmri.24726ISI: 000354738100008PubMedID: 25111561OAI: oai:DiVA.org:liu-109319DiVA: diva2:737447
Available from: 2014-08-12 Created: 2014-08-12 Last updated: 2017-12-05Bibliographically approved

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Karlsson, AnetteRomu, ThobiasBorga, MagnusDahlqvist Leinhard, Olof

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Karlsson, AnetteRomu, ThobiasBorga, MagnusDahlqvist Leinhard, Olof
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Medical InformaticsThe Institute of TechnologyCenter for Medical Image Science and Visualization (CMIV)Division of Radiological SciencesFaculty of Health SciencesDepartment of Radiation Physics
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Journal of Magnetic Resonance Imaging
Radiology, Nuclear Medicine and Medical ImagingMedical Image Processing

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